首先介绍了空间参考模型和坐标变换软件系统设计和实现的原则，并给出了软件系统的体系结构和功能模块组成。
This paper first introduces the principles of the design and implementation as well as the architecture and the functional modules of the software system.
针对如何快速求取空间点到STL模型表面有符号距离这一问题，提出一种基于线性八叉树的参考球方法。
For fast calculating the signed distance from spatial point to STL model, a reference ball method was put foward based on linear octree.
试验结果验证了模型和计算公式的正确性，可为空间目标探测光学系统的设计提供了设计参考。
In the end the correctness of the model and formula are proved by test, so it can provide reference to optical system design used in space un-illuminant targets detection.
结论：空间参考记忆和空间工作记忆是检测ad模型的可靠方法。
Conclusion: The spatial reference memory and spatial working memory are reliable methods to examine AD model.
以隔离型对称半桥双向变换器为对象，建立了以原边为参考的4种模式下的简化电路，提出了结合开关函数的状态空间平均模型的建立方法。
For isolated-type symmetry half-bridge bidirectional converter with phase-shifted control, a simplified circuit under 4 modes using the primary windings of transformer as reference object is built.
参考某些空间拦截器的构造形式，给出了空间拦截器的概念模型。
Consulting the structure of the some space intercepting device, the conceptual model of the space interceptor is provided.
目的：损伤大鼠双侧基底核形成阿尔茨海默病(AD)模型，用空间参考记忆和空间工作记忆共同检测该模型的可靠性。
Objective: To explore the reliability of Alzheimer's disease, AD model in rats with spatial reference memory and spatial working memory.
根据普适计算的特征，提出一个建设图书馆智能空间的参考模型。
This paper is to advocate the application of pervasive computing to the library management and the establishment of library smart space.
结果：模型组与青年组、老年组相比，空间参考记忆和空间工作记忆均明显下降（P<0.01）。
Results: The spatial reference memory and spatial working memory of the model group declined more significantly than those of the young and senile control groups , P<0.01).
集成神经网络模型以故障层次模型为参考，可以大大缩小诊断推理的求解空间，最终快速定位发生故障的根本部位。
Refer to hierarchical fault model, the integrated ANN diagnostic model can contract the scope of diagnostic reasoning, and find quickly the fault components.
行为数据集的来源越丰富、预测模型就越能获得理想的施展空间，从而为未来可能出现的更为广泛的潜在场景提供更具参考价值的预测结论。
Predictive models thrive on the richness of the source behavioral data sets, in order to drive more accurate predictions across a wider range of future scenarios.
行为数据集的来源越丰富、预测模型就越能获得理想的施展空间，从而为未来可能出现的更为广泛的潜在场景提供更具参考价值的预测结论。
Predictive models thrive on the richness of the source behavioral data sets, in order to drive more accurate predictions across a wider range of future scenarios.
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